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种子名称： Modern Artificial Intelligence Masterclass Build 6 Projects
文件类型： 视频
文件数目： 84个文件
文件大小： 8.42 GB
收录时间： 2024-1-10 03:48
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Modern Artificial Intelligence Masterclass Build 6 Projects.torrent

3. Emotion AI/7. Task #6 - Understand Artificial Neural Networks (ANNs) Theory & Intuition.mp4219.47MB

4. AI in Healthcare/1. Project Introduction and Welcome Message.mp458.01MB

4. AI in Healthcare/7. Task #6 - Train a Classifier Model To Detect Brain Tumors.mp4201.36MB

4. AI in Healthcare/5. Task #4 - Understand the Intuition behind ResNet and CNNs.mp4122.27MB

4. AI in Healthcare/4. Task #3 - Visualize and Explore Datasets.mp4164.87MB

4. AI in Healthcare/3. Task #2 - Import Libraries and Datasets.mp4107.07MB

4. AI in Healthcare/11. Task #10 - Train ResUnet Segmentation Model.mp438.29MB

4. AI in Healthcare/9. Task #8 - Understand ResUnet Segmentation Models Intuition.mp4150.52MB

4. AI in Healthcare/10. Task #9 - Build a Segmentation Model to Localize Brain Tumors.mp4136.71MB

4. AI in Healthcare/8. Task #7 - Assess Trained Classifier Model Performance.mp479.19MB

4. AI in Healthcare/2. Task #1 - Understand the Problem Statement and Business Case.mp4175.95MB

4. AI in Healthcare/6. Task #5 - Understand Theory and Intuition Behind Transfer Learning.mp4120.68MB

6. AI In Business (Finance) & AutoML/7. Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm.mp4212.63MB

6. AI In Business (Finance) & AutoML/11. Task #9 - Understand XG-Boost in AWS SageMaker.mp477.68MB

6. AI In Business (Finance) & AutoML/1. Project Introduction and Welcome Message.mp456.98MB

6. AI In Business (Finance) & AutoML/9. Task #7 - Train XG-Boost Algorithm Using Scikit-Learn.mp471.48MB

6. AI In Business (Finance) & AutoML/6. Task #4 - Clean Up the Data.mp455.6MB

6. AI In Business (Finance) & AutoML/13. Task #11 - Deploy Model and Make Inference.mp4107.9MB

6. AI In Business (Finance) & AutoML/10. Task #8 - Perform Grid Search and Hyper-parameters Optimization.mp465.7MB

6. AI In Business (Finance) & AutoML/5. Task #3 - Visualize and Explore Dataset.mp4199.67MB

6. AI In Business (Finance) & AutoML/12. Task #10 - Train XG-Boost in AWS SageMaker.mp4140.4MB

6. AI In Business (Finance) & AutoML/8. Task #6 - Understand XG-Boost Algorithm Key Steps.mp4205.48MB

6. AI In Business (Finance) & AutoML/4. Task #2 - Import Libraries and Datasets.mp451.86MB

6. AI In Business (Finance) & AutoML/14. Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!).mp4122.81MB

6. AI In Business (Finance) & AutoML/3. Task #1 - Understand the Problem Statement & Business Case.mp4105.46MB

7. Creative AI/1. Project Introduction and Welcome Message.mp437.07MB

7. Creative AI/2. Task #1 - Understand the Problem Statement & Business Case.mp4136.85MB

7. Creative AI/10. Task #9 - Apply DeepDream Algorithm to Generate Images.mp466.9MB

7. Creative AI/9. Task #8 - Implement Deep Dream Algorithm Part #2.mp4120.75MB

7. Creative AI/3. Task #2 - Import Model with Pre-trained Weights.mp453.87MB

7. Creative AI/4. Task #3 - Import and Merge Images.mp467.98MB

7. Creative AI/6. Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm.mp4195.03MB

7. Creative AI/11. Task #10 - Generate DeepDream Video.mp477.81MB

7. Creative AI/7. Task #6 - Understand The Gradient Operations in TF 2.0.mp437.47MB

7. Creative AI/5. Task #4 - Run the Pre-trained Model and Explore Activations.mp485.05MB

7. Creative AI/8. Task #7 - Implement Deep Dream Algorithm Part #1.mp483.08MB

8. Explainable AI/1. Project Introduction and Welcome Message.mp439.61MB

9. Crash Course on AWS, S3, and SageMaker/7. AWS SageMaker Overview.mp464.64MB

9. Crash Course on AWS, S3, and SageMaker/2. Key Machine Learning Components and AWS Tour.mp460.76MB

9. Crash Course on AWS, S3, and SageMaker/5. EC2 and Identity and Access Management (IAM).mp4108.29MB

9. Crash Course on AWS, S3, and SageMaker/4. Amazon S3.mp4111.36MB

9. Crash Course on AWS, S3, and SageMaker/3. Regions and Availability Zones.mp452.94MB

9. Crash Course on AWS, S3, and SageMaker/9. AWS SageMaker Studio Overview.mp466.93MB

9. Crash Course on AWS, S3, and SageMaker/6. AWS Free Tier Account Setup and Overview.mp438.11MB

9. Crash Course on AWS, S3, and SageMaker/1. What is AWS and Cloud Computing.mp468.06MB

9. Crash Course on AWS, S3, and SageMaker/8. AWS SageMaker Walk-through.mp481.6MB

9. Crash Course on AWS, S3, and SageMaker/11. AWS SageMaker Model Deployment.mp4110.86MB

9. Crash Course on AWS, S3, and SageMaker/10. AWS SageMaker Studio Walk-through.mp451.51MB

3. Emotion AI/9. Task #8 - Understand Convolutional Neural Networks and ResNets.mp4127.04MB

3. Emotion AI/10. Task #9 - Build ResNet to Detect Key Facial Points.mp4131.85MB

3. Emotion AI/1. Project Introduction and Welcome Message.mp461.4MB

3. Emotion AI/2. Task #1 - Understand the Problem Statement & Business Case.mp4118.88MB

3. Emotion AI/13. Task #12 - Import and Explore Facial Expressions (Emotions) Datasets.mp494.82MB

3. Emotion AI/15. Task #14 - Perform Image Augmentation.mp4109.35MB

3. Emotion AI/21. Task #20 - Serve Trained Model in TensorFlow 2.0 Serving.mp441.17MB

3. Emotion AI/17. Task #16 - Understand Classifiers Key Performance Indicators (KPIs).mp4135.26MB

3. Emotion AI/16. Task #15 - Build & Train a Facial Expression Classifier Model.mp4138.26MB

3. Emotion AI/8. Task #7 - Understand ANNs Training & Gradient Descent Algorithm.mp4160.52MB

3. Emotion AI/3. Task #2 - Import Libraries and Datasets.mp4102.22MB

3. Emotion AI/14. Task #13 - Visualize Images for Facial Expression Detection.mp455.97MB

3. Emotion AI/20. Task #19 - Save Trained Model for Deployment.mp4101.84MB

3. Emotion AI/22. Task #21 - Deploy Both Models and Make Inference.mp488.5MB

4. AI in Healthcare/12. Task #11 - Assess Trained ResUNet Segmentation Model Performance.mp4128.67MB

3. Emotion AI/5. Task #4 - Perform Images Augmentation.mp4141.82MB

3. Emotion AI/18. Task #17 - Assess Facial Expression Classifier Model.mp4104.52MB

3. Emotion AI/12. Task #11 - Assess Trained ResNet Model Performance.mp442.91MB

3. Emotion AI/6. Task #5 - Perform Data Normalization and Scaling.mp459.34MB

3. Emotion AI/19. Task #18 - Make Predictions from Both Models 1. Key Facial Points & 2. Emotion.mp460.04MB

3. Emotion AI/4. Task #3 - Perform Image Visualizations.mp487.34MB

3. Emotion AI/11. Task #10 - Compile and Train Facial Key Points Detector Model.mp468.11MB

1. Introduction/1. Introduction and Welcome Message.mp469.17MB

1. Introduction/3. Course Outline and Key Learning Outcomes.mp4174.78MB

1. Introduction/2. Introduction, Key Tips and Best Practices.mp4108.49MB

5. AI in Business (Marketing)/8. Task #7 - Apply K-Means Clustering Algorithm.mp4145.46MB

5. AI in Business (Marketing)/1. Project Introduction and Welcome Message.mp446.85MB

5. AI in Business (Marketing)/4. Task #3 - Perform Exploratory Data Analysis (Part #1).mp4132.99MB

5. AI in Business (Marketing)/7. Apply Elbow Method to Find the Optimal Number of Clusters.mp472.65MB

5. AI in Business (Marketing)/3. Task #2 - Import Libraries and Datasets.mp4106.54MB

5. AI in Business (Marketing)/9. Task #8 - Understand Intuition Behind Principal Component Analysis (PCA).mp4100.97MB

5. AI in Business (Marketing)/5. Task #4 - Perform Exploratory Data Analysis (Part #2).mp4182.96MB

5. AI in Business (Marketing)/6. Task #5 - Understand Theory and Intuition Behind K-Means Clustering Algorithm.mp4165.3MB

5. AI in Business (Marketing)/11. Task #10 - Apply Auto-encoders and Perform Clustering.mp4135.32MB

5. AI in Business (Marketing)/10. Task #9 - Understand the Theory and Intuition Behind Auto-encoders.mp483.04MB

5. AI in Business (Marketing)/2. Task #1 - Understand AI Applications in Marketing.mp473.74MB